East Palo Alto Planning: ADU Analysis

The following map shows all buildable area for attached and detached ADUs in East Palo Alto.

• Hover over parcels to see addresses. Existing buildings and buildable area are only mapped for residential parcels.
• The green region is detached ADU buildable area. It’s 4ft from side/rear, 6ft from existing buildings, no closer to the street than the existing building, and can fit at least an 8ft x 20ft structure. Click to see the maximum detached ADU that can be built on the green area of the parcel. This is capped at 1,200 sqft per state regulations, even if the green space is much larger. Hover over to see the sqft of the buildable area.
• The blue shape is an example detached ADU. For now, this just shows the smallest possible 8ft x 20ft ADU, generally set as far as possible away from existing structures. We’ll be updating this shortly with the biggest “reasonable” size and shape ADU.
• The yellow region (including green) is attached ADU buildable area. It doesn’t have the 6ft setback from existing buildings. Click to see the maximum attached ADU that can be built on the parcel. This is capped at 50% of existing gross building sqft or 1,200 sqft. Hover over to see the sqft of the buildable area.
• This Drive folder has the raw data (including owner names and many Assessor building characteristics) in CSV form, as well as shapefile versions based on parcel geometry, building geometry, and attached/detached buildable area geometries.
• More information about the methodology and data sources will be prepared in an Appendix soon.

load("epa_parcels_furthest_adu.Rdata")

map <- epa_parcels_furthest_adu

leaflet() %>%
  addTiles(group = "Default") %>% 
  addProviderTiles(providers$Esri.WorldImagery, group = "Satellite") %>% 
  addPolygons(
    data = map %>% st_set_geometry("parcel_geometry") %>% dplyr::select(ADDRESS) %>% st_transform(4326),
    fill = F, 
    color = "white",
    weight = 0.5,
    opacity = 0.5,
    highlightOptions = highlightOptions(
      weight = 2,
      opacity = 1
    ),
    label = ~ADDRESS,
    group = "Parcels"
  ) %>% 
  addPolygons(
    data = map %>% st_set_geometry("attached_buildable_area_geometry") %>% dplyr::select(max_attached_buildable_area) %>% st_transform(4326) %>% filter(!is.na(st_dimension(.))),
    fillColor = "yellow", 
    stroke = F,
    fillOpacity = 0.5,
    highlightOptions = highlightOptions(
      fillOpacity = 1
    ),
    label = ~max_attached_buildable_area,
    group = "Attached ADU Buildable Area"
  ) %>% 
  addPolygons(
    data = map %>% st_set_geometry("detached_buildable_area_geometry") %>% dplyr::select(max_detached_buildable_area) %>% st_transform(4326) %>% filter(!is.na(st_dimension(.))),
    fillColor = "green", 
    stroke = F,
    fillOpacity = 0.5,
    highlightOptions = highlightOptions(
      fillOpacity = 1
    ),
    label = ~max_detached_buildable_area,
    group = "Detached ADU Buildable Area"
  ) %>% 
  addPolygons(
    data = map %>% st_set_geometry("building_geometry") %>% dplyr::select(`GROSS BUILDING SQFT`) %>% st_transform(4326) %>% filter(!is.na(st_dimension(.))),
    fillColor = "tan", 
    stroke = F,
    fillOpacity = 0.5,
    highlightOptions = highlightOptions(
      fillOpacity = 1
    ),
    label = ~`GROSS BUILDING SQFT`,
    group = "Existing Building"
  ) %>% 
  addPolygons(
    data = map %>% st_set_geometry("furthest_adu") %>% st_transform(4326) %>% filter(!is.na(st_dimension(.))),
    fillColor = "blue", 
    stroke = F,
    fillOpacity = 0.5,
    highlightOptions = highlightOptions(
      fillOpacity = 1
    ),
    group = "Example Detached ADU"
  ) %>% 
  addLayersControl(
    baseGroups = c("Default", "Satellite"),
    overlayGroups = c("Parcels", "Existing Building", "Attached ADU<br>Buildable Area", "Detached ADU<br>Buildable Area", "Example<br>Detached ADU"),
    options = layersControlOptions(collapsed = T)
  )

# include_url("https://city.systems/epa-adu/epa_parcels_adus_map.html")

\(~\)

Next are some summary statistics.

First, here’s the breakdown of parcels by zoning type in General Plan 2035. The parcel shapes and zoning were pulled from ArcGISOnline. Note there were some inconsistencies in APN designation between this zoning file and the County’s Assessor record. 6 residential parcels were manually re-coded from Assessor APN to EPA General Plan APN.

zoning_summary <-
  epa_parcels_furthest_adu %>%
  st_set_geometry(NULL) %>% 
  group_by(Zoning) %>% 
  summarize(
    Count = n(),
    `Median Lot Size` = median(parcel_area, na.rm=T) %>% round()
  ) %>% 
  filter(!is.na(Zoning))
  
kable(
  zoning_summary, 
  booktabs = TRUE,
  caption = 'Zoning summary'
  ) %>%
  kable_styling() %>%
  scroll_box(width = "100%")

Zoning summary

Zoning	Count	Median Lot Size
4 Corners	41	9813
Bay Road Central	28	10184
C-G (Commercial General)	9	17606
C-N (Commercial Neighborhood)	15	8573
C-O (Commercial Office)	12	16029
Industrial Flex Overlay	12	13883
Industrial Transition	17	13654
MUC-1 (Mixed Use Corridor)	172	9994
MUC-2 (Mixed Use Corridor)	8	12986
MUH (Mixed Use High)	12	38825
MUL (Mixed Use Low)	31	8114
PI (Public Institutional)	19	81278
PR (Parks and Recreation)	34	23476
PUD (Planned Unit Development)	219	3102
R-HD (Multi-Family High Density Residential)	284	30208
R-LD (Single-Family Residential)	3518	5603
R-MD-1 (Multi-Family Medium Density Residential)	300	6244
R-MD-2 (Multi-Family Medium Density Residential)	155	6667
R-UHD (Multi-Family Urban High Density Residential)	46	30978
REC (Ravenswood Employment Center)	30	40473
RM (Resource Management)	5	228188
Urban Residential	81	10151
Waterfront Office	11	85561

\(~\)

New state regs require ADUs to be allowed in all residentially zoned parcels. We select: R-HD, R-LD, R-MD-1, R-MD-2, R-UHD, & Urban Residential.

The following table is the same as above but just for residential zones, and adding existing structure size and special flood hazard area status.

residential_summary <-
  epa_parcels_furthest_adu %>%
  st_set_geometry(NULL) %>% 
  filter(
    Zoning %in% 
      c(
        "R-HD (Multi-Family High Density Residential)",
        "R-LD (Single-Family Residential)",
        "R-MD-1 (Multi-Family Medium Density Residential)",
        "R-MD-2 (Multi-Family Medium Density Residential)",
        "R-UHD (Multi-Family Urban High Density Residential)",
        "Urban Residential"
      )
  ) %>% 
  group_by(Zoning) %>% 
  summarize(
    Count = n(),
    `Median Lot Size` = median(parcel_area, na.rm=T) %>% round(),
    `Median Gross Bldg Sqft` = median(`GROSS BUILDING SQFT`, na.rm=T) %>% round(),
    `In Flood Zone` = sum(!is.na(FLD_ZONE))
  ) %>% 
  filter(!is.na(Zoning))

# hist(epa_parcels_adus %>% filter(Zoning == "R-LD (Single-Family Residential)") %>% pull(parcel_area), breaks=c(seq(0,1000000,500)),xlim = c(0,10000))

kable(
  residential_summary, 
  booktabs = TRUE,
  caption = 'Residential zoning summary'
  ) %>%
  kable_styling() %>%
  scroll_box(width = "100%")

Residential zoning summary

Zoning	Count	Median Lot Size	Median Gross Bldg Sqft	In Flood Zone
R-HD (Multi-Family High Density Residential)	284	30208	10658	35
R-LD (Single-Family Residential)	3518	5603	1110	1171
R-MD-1 (Multi-Family Medium Density Residential)	300	6244	2072	101
R-MD-2 (Multi-Family Medium Density Residential)	155	6667	1340	0
R-UHD (Multi-Family Urban High Density Residential)	46	30978	26408	0
Urban Residential	81	10151	1690	7

\(~\)

Of residentially zoned parcels, below is the breakdown of property use code according to the County Assessor, which should represent as of early 2019 the existing use. The table also notes which PUCs we considered to be “ADU eligible” for our analysis, and completed the buildable area analysis for. Note the following key caveats:

• PUC 91 and 92 are likely existing permitted ADU parcels. There are likely many other unpermitted ADUs under PUC 1.
• If a residentially zoned lot is currently vacant (PUC: 0), buildable area analysis wasn’t performed. But if the property owner were to build a residential building, then it’s likely they would also subsequently be able to build an ADU. So our ADU numbers will be underestimates because they don’t include currently vacant residential lots.
• Larger multifamily buildings (5+ units) are not included in the buildable area analysis, although they are technically ADU eligible. Such buildings are typically very differently designed than low-density housing, and have their own special state ADU regulations. We would assume that most of the ADU opportunities for such buildings are internal ADU conversions.

The table includes some additional statistics. % owner occupied is the number for which there is a listed homeowner tax exemption OR the owner’s mailing address matches the property address.

residential_puc_summary <-
  epa_parcels_furthest_adu %>%
  st_set_geometry(NULL) %>% 
  filter(
    Zoning %in% 
      c(
        "R-HD (Multi-Family High Density Residential)",
        "R-LD (Single-Family Residential)",
        "R-MD-1 (Multi-Family Medium Density Residential)",
        "R-MD-2 (Multi-Family Medium Density Residential)",
        "R-UHD (Multi-Family Urban High Density Residential)",
        "Urban Residential"
      )
  ) %>% 
  group_by(PUC) %>% 
  summarize(
    Count = n(),
    `Median Lot Size` = median(parcel_area, na.rm=T) %>% round(),
    `Median Gross Bldg Sqft` = median(`GROSS BUILDING SQFT`, na.rm=T) %>% round(),
    `In Flood Zone` = sum(!is.na(FLD_ZONE)),
    `# of Units` = sum(UNITS,na.rm=T),
    `% Owner Occupied` = sum(`EXEMPTION CODE`=="HO" | ADDRESS != substr(`OWNER MAILING ADDRESS`,1,nchar(ADDRESS)),na.rm=T)/n()*100,
    `% Owner Occupied` = `% Owner Occupied` %>% round()
  ) %>% 
  filter(!is.na(PUC)) %>% 
  filter(PUC <= 5 | PUC >= 89) %>% 
  left_join(read_csv("smc_puc.csv"), by="PUC") %>% 
  dplyr::select(PUC, `PUC Description`, Categorization = type, everything())

kable(
  residential_puc_summary, 
  booktabs = TRUE,
  caption = 'Residential PUC summary'
  ) %>%
  kable_styling() %>%
  scroll_box(width = "100%")

Residential PUC summary

PUC	PUC Description	Categorization	Count	Median Lot Size	Median Gross Bldg Sqft	In Flood Zone	# of Units	% Owner Occupied
0	VACANT LAND	other	69	6112	NA	13	0	99
1	SINGLE FAMILY RES	adu eligible	3603	5561	1110	1157	0	78
2	DUPLEX	adu eligible	49	5996	1990	12	86	94
3	TRIPLEX	adu eligible	3	4997	1895	0	9	100
4	FOURPLEX	adu eligible	9	7129	2836	5	40	100
5	FIVE OR MORE UNITS	other residential	85	19993	18018	22	1854	99
89	RESIDENTIAL MISC.	adu eligible	2	7583	0	0	0	50
91	MORE THAN 1 DETACHED LIVING UNITS	adu eligible	27	7524	2181	5	27	85
92	SFR CONVERTED TO 2 UNITS	adu eligible	38	6582	2210	12	28	89
93	SFR & DUPLEX OR TRIPLEX	adu eligible	4	9001	2950	3	7	100
94	TWO DUPLEXES	adu eligible	6	7033	2388	3	24	100
95	RESIDENTIAL; COMBINATION OF UNIT TYPES	adu eligible	7	8211	2699	4	25	86
96	FOURPLEX PLUS A RESIDENCE, DUPLEX OR TRI	adu eligible	6	9593	4810	4	39	100
97	RESIDENTIAL CONDO	other residential	279	154490	NA	51	0	85

\(~\)

The following shows ADU statistics for the residential parcels.

epa_parcels_adus_residential <-
  epa_parcels_furthest_adu %>%
  st_set_geometry(NULL) %>% 
  filter(
    Zoning %in% 
      c(
        "R-HD (Multi-Family High Density Residential)",
        "R-LD (Single-Family Residential)",
        "R-MD-1 (Multi-Family Medium Density Residential)",
        "R-MD-2 (Multi-Family Medium Density Residential)",
        "R-UHD (Multi-Family Urban High Density Residential)",
        "Urban Residential"
      )
  )

epa_parcels_adus_residential_no9192 <-
  epa_parcels_adus_residential %>% 
  filter(!PUC %in% c(91,92)) %>% 
  filter(PUC <= 5 | PUC >= 89)

residential_adu_summary <-
  rbind(
    data.frame(
      Description = "Total # of Parcels",
      Amount = epa_parcels_adus_residential %>% nrow(),
      `Amount in Flood Zone` = epa_parcels_adus_residential %>% filter(!is.na(FLD_ZONE)) %>% nrow()
    ),
    data.frame(
      Description = "Total # of ADU-Eligible Parcels",
      Amount = epa_parcels_adus_residential %>% filter(PUC <= 5 | PUC >= 89) %>%  nrow(),
      `Amount in Flood Zone` = epa_parcels_adus_residential %>% filter(!PUC %in% c(91,92)) %>% filter(PUC <= 5 | PUC >= 89) %>% filter(!is.na(FLD_ZONE)) %>% nrow()
    ),
    data.frame(
      Description = "Estimated # of Permitted ADUs",
      Amount = epa_parcels_adus_residential %>% filter(PUC %in% c(91,92)) %>%  nrow(),
      `Amount in Flood Zone` = epa_parcels_adus_residential %>% filter(PUC %in% c(91,92)) %>% filter(!is.na(FLD_ZONE)) %>% nrow()
    ),
    data.frame(
      Description = "Estimated # of Ministerial JADUs",
      Amount = epa_parcels_adus_residential_no9192 %>% nrow(),
      `Amount in Flood Zone` = epa_parcels_adus_residential_no9192 %>% filter(!is.na(FLD_ZONE)) %>% nrow()
    ),
    data.frame(
      Description = "Estimated # of Ministerial Attached/Detached ADUs (up to 800sqft)",
      Amount = epa_parcels_adus_residential_no9192 %>% filter(max_attached_buildable_area <= 800 | max_detached_buildable_area <= 800) %>% nrow(),
      `Amount in Flood Zone` = epa_parcels_adus_residential_no9192 %>% filter(max_attached_buildable_area <= 800 | max_detached_buildable_area <= 800) %>% filter(!is.na(FLD_ZONE)) %>% nrow()
    ),
    data.frame(
      Description = "Estimated # of Ministerial Attached ADUs (up to 800sqft)",
      Amount = epa_parcels_adus_residential_no9192 %>% filter(max_attached_buildable_area <= 800) %>% nrow(),
      `Amount in Flood Zone` = epa_parcels_adus_residential_no9192 %>% filter(max_attached_buildable_area <= 800) %>% filter(!is.na(FLD_ZONE)) %>% nrow()
    ),
    data.frame(
      Description = "Estimated # of Ministerial Detached ADUs (up to 800sqft)",
      Amount = epa_parcels_adus_residential_no9192 %>% filter(max_detached_buildable_area <= 800) %>% nrow(),
      `Amount in Flood Zone` = epa_parcels_adus_residential_no9192 %>% filter(max_detached_buildable_area <= 800) %>% filter(!is.na(FLD_ZONE)) %>% nrow()
    ),
    data.frame(
      Description = "Estimated # of Parcels under Local Influence (800-1200sqft)",
      Amount = epa_parcels_adus_residential_no9192 %>% filter(max_attached_buildable_area > 800 | max_detached_buildable_area > 800) %>% nrow(),
      `Amount in Flood Zone` = epa_parcels_adus_residential_no9192 %>% filter(max_attached_buildable_area > 800 | max_detached_buildable_area > 800) %>% filter(!is.na(FLD_ZONE)) %>% nrow()
    ),
    data.frame(
      Description = "Estimated # of Attached ADUs under Local Influence (800-1200sqft)",
      Amount = epa_parcels_adus_residential_no9192 %>% filter(max_attached_buildable_area > 800) %>% nrow(),
      `Amount in Flood Zone` = epa_parcels_adus_residential_no9192 %>% filter(max_attached_buildable_area > 800) %>% filter(!is.na(FLD_ZONE)) %>% nrow()
    ),
    data.frame(
      Description = "Estimated # of Detached ADUs under Local Influence (800-1200sqft)",
      Amount = epa_parcels_adus_residential_no9192 %>% filter(max_detached_buildable_area > 800) %>% nrow(),
      `Amount in Flood Zone` = epa_parcels_adus_residential_no9192 %>% filter(max_detached_buildable_area > 800) %>% filter(!is.na(FLD_ZONE)) %>% nrow()
    )
  ) %>% 
  rename(`Amount in Flood Zone` = Amount.in.Flood.Zone)

kable(
  residential_adu_summary, 
  booktabs = TRUE,
  caption = 'Residential ADU summary'
  ) %>%
  kable_styling() %>%
  scroll_box(width = "100%")

Residential ADU summary

Description	Amount	Amount in Flood Zone
Total # of Parcels	4384	1314
Total # of ADU-Eligible Parcels	4187	1274
Estimated # of Permitted ADUs	65	17
Estimated # of Ministerial JADUs	4122	1274
Estimated # of Ministerial Attached/Detached ADUs (up to 800sqft)	3125	1055
Estimated # of Ministerial Attached ADUs (up to 800sqft)	2977	1016
Estimated # of Ministerial Detached ADUs (up to 800sqft)	1228	392
Estimated # of Parcels under Local Influence (800-1200sqft)	1849	664
Estimated # of Attached ADUs under Local Influence (800-1200sqft)	421	125
Estimated # of Detached ADUs under Local Influence (800-1200sqft)	1692	621

\(~\)

Here’s a map showing some of the different circumstances from the table above. You can turn the flood layer on and off.

• Yellow: Detached ADUs under Local Influence (800-1200sqft)
• Orange: Attached ADUs under Local Influence (800-1200sqft)
• Purple: Existing Permitted ADU
• Green: Ministerial ADU

adu_summary_map <-
  epa_parcels_furthest_adu %>%
  mutate(
    Category =
      case_when(
        PUC %in% c(91,92) ~ "Existing Permitted ADU",
        max_detached_buildable_area > 800 ~ "Detached ADUs under Local Influence (800-1200sqft)",
        max_attached_buildable_area > 800 ~ "Attached ADUs under Local Influence (800-1200 sqft)",
        max_detached_buildable_area <= 800 ~ "Ministerial Detached ADUs (up to 800 sqft)",
        max_attached_buildable_area <= 800 ~ "Ministerial Attached ADUs (up to 800 sqft)",
        Zoning %in% 
      c(
        "R-HD (Multi-Family High Density Residential)",
        "R-LD (Single-Family Residential)",
        "R-MD-1 (Multi-Family Medium Density Residential)",
        "R-MD-2 (Multi-Family Medium Density Residential)",
        "R-UHD (Multi-Family Urban High Density Residential)",
        "Urban Residential"
      ) & (PUC <= 5 | PUC >= 89) ~ "Ministerial JADUs",
        TRUE ~ "Other"
      )
  ) %>% 
  mutate(
    Category = ifelse(Category == "Other", NA, Category)
  ) %>% 
  dplyr::select(ADDRESS,Category)

load("epa_sfha.Rdata")

epa_boundary <-
  places("CA", cb=FALSE) %>% 
  filter(NAME == "East Palo Alto") %>% 
  st_transform(projection)

epa_sfha_clip <-
  st_intersection(epa_sfha, epa_boundary)

leaflet() %>% 
  addTiles(group = "Default") %>% 
  addProviderTiles(providers$Esri.WorldImagery, group = "Satellite") %>% 
  addPolygons(
    data = adu_summary_map %>% filter(Category == "Existing Permitted ADU") %>% st_transform(4326),
    fillColor = "purple",
    color = "white",
    weight = 0.5,
    opacity = 0.5,
    fillOpacity = 0.75,
    highlightOptions = highlightOptions(
      weight = 2,
      opacity = 1
    ),
    label = ~ADDRESS,
    group = "Existing Permitted ADU"
  ) %>% 
  addPolygons(
    data = adu_summary_map %>% filter(Category == "Detached ADUs under Local Influence (800-1200sqft)") %>% st_transform(4326),
    fillColor = "yellow",
    color = "white",
    weight = 0.5,
    opacity = 0.5,
    fillOpacity = 0.5,
    highlightOptions = highlightOptions(
      weight = 2,
      opacity = 1
    ),
    label = ~ADDRESS,
    group = "Detached ADUs under Local Influence (800-1200sqft)"
  ) %>% 
  addPolygons(
    data = adu_summary_map %>% filter(Category == "Attached ADUs under Local Influence (800-1200 sqft)") %>% st_transform(4326),
    fillColor = "orange",
    color = "white",
    weight = 0.5,
    opacity = 0.5,
    fillOpacity = 0.75,
    highlightOptions = highlightOptions(
      weight = 2,
      opacity = 1
    ),
    label = ~ADDRESS,
    group = "Attached ADUs under Local Influence (800-1200sqft)"
  ) %>% 
  addPolygons(
    data = adu_summary_map %>% filter(Category == "Ministerial Detached ADUs (up to 800 sqft)") %>% st_transform(4326),
    fillColor = "green",
    color = "white",
    weight = 0.5,
    opacity = 0.5,
    fillOpacity = 0.75,
    highlightOptions = highlightOptions(
      weight = 2,
      opacity = 1
    ),
    label = ~ADDRESS,
    group = "Ministerial Detached ADUs (up to 800 sqft)"
  ) %>% 
  addPolygons(
    data = adu_summary_map %>% filter(Category == "Ministerial Attached ADUs (up to 800 sqft)") %>% st_transform(4326),
    fillColor = "green",
    color = "white",
    weight = 0.5,
    opacity = 0.5,
    fillOpacity = 0.75,
    highlightOptions = highlightOptions(
      weight = 2,
      opacity = 1
    ),
    label = ~ADDRESS,
    group = "Ministerial Attached ADUs (up to 800 sqft)"
  ) %>% 
  addPolygons(
    data = adu_summary_map %>% filter(Category == "Ministerial JADUs") %>% st_transform(4326),
    fillColor = "green",
    color = "white",
    weight = 0.5,
    opacity = 0.5,
    fillOpacity = 0.75,
    highlightOptions = highlightOptions(
      weight = 2,
      opacity = 1
    ),
    label = ~ADDRESS,
    group = "Ministerial JADUs"
  ) %>% 
  addPolygons(
    data = epa_sfha_clip %>% st_transform(4326),
    fillColor = "blue",
    stroke = F,
    fillOpacity = 0.25,
    group = "Special Flood Hazard Area"
  ) %>% 
  addLayersControl(
    baseGroups = c("Default", "Satellite"),
    overlayGroups = c("Existing Permitted ADU","Detached ADUs under<br>Local Influence (800-1200sqft)", "Attached ADUs under<br>Local Influence (800-1200sqft)","Ministerial Detached<br>ADUs (up to 800 sqft)","Ministerial Attached<br>ADUs (up to 800 sqft)", "Ministerial JADUs","Special Flood Hazard Area"),
    options = layersControlOptions(collapsed = T)
  )

\(~\)

Here’s the distribution of buildable area for attached ADUs.

hist(epa_parcels_furthest_adu$max_attached_buildable_area, breaks=c(seq(0,1200,50)),xlim = c(0,1200))

\(~\)

Here’s the distribution of buildable area for detached ADUs.

hist(epa_parcels_furthest_adu$max_detached_buildable_area, breaks=c(seq(0,1200,50)),xlim = c(0,1200))

\(~\)

More summary statistics coming soon.